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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

HPC-NMF: A High-Performance Parallel Algorithm for Nonnegative Matrix Factorization

NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient distributed algorithms to solve the problem for big data sets. We propose a high-performance distributed-memory parallel algorithm that computes the factorization by iteratively solving alternating non-negative least squares (NLS) subproblems for $\WW$ and $\HH$. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). As opposed to previous implementation, our algorithm is also flexible: It performs well for both dense and sparse matrices, and allows the user to choose any one of the multiple algorithms for solving the updates to low rank factors $\WW$ and $\HH$ within the alternating iterations.

Kannan, Ramakrishnan↗
DOE OSTI2025

Improving the Transportability of a Deep Learning Denoising Model Using Transfer Learning Techniques

The adoption of machine learning techniques in the seismology community has led to great performance improvements in several areas, including signal processing. Specifically, the development of deep learning–based seismic waveform denoising models has the potential to yield improvements in signal detection capabilities for networks operating in particularly noisy environments. Recent advancements in the design of these deep learning denoising models have included the incorporation of continuous and discrete wavelet transform functions into the network architecture to improve the learning capabilities and efficiency of said models. These wavelet transform–based seismic denoising models have shown improved denoising capabilities in regions where there is good agreement between the data features present in the training and evaluation datasets. However, questions remain about the overall transportability of these models to other monitoring regions. Here, in this study, we will determine the baseline transportability of a newly developed multilevel wavelet‐transform convolutional neural network (MWCNN) seismic denoising model. We accomplish this by taking a version of the MWCNN denoising model trained on data collected from the Utah region and evaluating its denoising performance on datasets collected from the neighboring Nevada region, which differ with regard to monitoring sensor types and event histories. We find that there is a notable variability in denoising performance related to the degree of similarity between the initial and new target datasets. The most notable difference in denoising performance is the ability of the denoising model to preserve accurate amplitude information associated with the signal energy present in the waveform data. Finally, we evaluate the ability of transfer learning techniques to improve the transportability of the MWCNN denoising model. We find that although there is still a performance gap present in the denoising results of the MWCNN model, transfer learning did yield improved results.

Quinones, Louis [Sandia National Laboratories (SNL↗
DOE OSTI2017

Understanding the Hierarchy of Dense Subgraphs in Stationary and Temporally Varying Setting

Graphs are widely used to model relationships in a wide variety of domains such as sociology, bioinformatics, infrastructure, the WWW, to name a few. One of the key observations is that while real-world graphs are often globally sparse, they are locally dense. In other words, the average degree is often quite small (say at most 10 in a million vertex graph), but vertex neighborhoods are often dense. Finding dense subgraphs is a critical aspect of graph mining It has been used for finding communities and spam link farms in web graphs, graph visualization, real-time story identification, DNA motif detection in biological networks, finding correlated genes, epilepsy prediction, finding price value motifs in financial data, graph compression, distance query indexing, and increasing the throughput of social networking site servers. However, most standard formulations of this problem (like clique, quasi-clique, k-densest subgraph) are NP-hard. Furthermore, current dense subgraph finding algorithms usually optimize some objective, and only find a few such subgraphs without providing any structural relations, whereas the goal is rarely to find the "true optimum," but to identify many (if not all) dense substructures, understand their distribution in the graph, and ideally determine relationships among them. In this project, we first aim to devise algorithms and provide 3 implementations with nice visualizations to find the hierarchy between dense subgraphs, and then understand the structure of the hierarchy to gain more insight on the hidden patterns in real-world networks. Another important aspects in graph analysis is the temporal nature of networks. Networks evolve over time and in many applications data arrives at a high velocity, and thus it is important to design algorithms that can process data efficiently. We report three main results towards identifying dense structures in large evolving graphs. First, we will show how the hierarchical connectedness structure can be maintained efficiently, where connectedness is defined by increasing levels of connectivity strength. Next, we present dense structure can be identified in bipartite graphs without building projection graphs. And finally, we present a new method for peeling algorithms This new approach avoids sequential nature of peeling algorithms and is amenable to parallelization, which is crucial for processing high velocity data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Precursor Analysis Report: Industroyer2 and Wiper Malware Targeting Ukrainian Energy Provider 2022

The Industroyer2 and Wiper Malware Targeting Ukrainian Energy Provider 2022 Precursor Analysis Report leverages publicly available information about the Industroyer2 cyber attack and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. An adversary attempted to cause a blackout in Ukraine in April 2022 by using the Industroyer2 malware against a regional Ukrainian energy provider. The adversary targeted eight high-voltage electrical substations and utilized the malware in tandem with disk wipers for Windows, Linux, and Solaris operating systems in an attempt to make response and recovery efforts more difficult. The adversary reused a piece of the original Industroyer malware designed to open circuit breakers and de-energize target substations. The adversary gained initial access to the victim’s enterprise network through unknown means in February 2022 and was able to perform reconnaissance, pivot to the operations network, and reside in the system for at least 51 days. This gave the adversary a detailed understanding of the environment and allowed them to customize the Industroyer2 malware to the victim’s operations network. However, defenders detected and stopped the attack before the adversary could achieve their intended impact. Had the Industroyer2 attack been successful, it could have caused a blackout for more than two million people during the early stages of Russia’s invasion of Ukraine. Researchers and analysts identified 22 unique techniques (used in a sequence of 31 steps) utilized during the attack with a total of 297 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Twenty-three of the identified techniques used during the Industroyer2 cyber attack were precursors to the triggering event. Analysis identified 224 observables associated with these precursor techniques, 122 of which were assessed to have an increased likelihood of being perceived in the 51 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Methods and Comparisons Between Computer Vision and Radar Based Vehicle Location

Measuring vehicle locations relative to a driver's vehicle is a critical component in the analysis of driving data from both postanalysis (such as in naturalistic driving studies) or in autonomous vehicle navigation. In this work we describe a method to estimate vehicle positions from a forward-looking video camera using intrinsic camera calibration, estimates of extrinsic parameters, and a convolutional neural network trained to detect and locate vehicles in video data. We compare the measurements we achieve with this method with ground truth and with radar data available from a naturalistic driving study. We identify regions where video is preferred, where radar is preferred, and explore trade-offs between the two methods in regions where the preference is more ambiguous. We describe applications of these measurements for transportation analysis.

Aykac, Deniz↗
DOE OSTI2022

Decision-Based Fusion for Vehicle Matching

In this work, a framework is proposed for decision fusion utilizing features extracted from vehicle images and their detected wheels. Siamese networks are exploited to extract key signatures from pairs of vehicle images. Our approach then examines the extent of reliance between signatures generated from vehicle images to robustly integrate different similarity scores and provide a more informed decision for vehicle matching. To that end, a dataset was collected that contains hundreds of thousands of side-view vehicle images under different illumination conditions and elevation angles. Experiments show that our approach could achieve better matching accuracy by taking into account the decisions made by a whole-vehicle or wheels-only matching network.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Ozone depletion in the Arctic and Antarctic stratosphere induced by wildfire smoke

Abstract. A record-breaking stratospheric ozone loss was observed over the Arctic and Antarctica in 2020. Strong ozone depletion occurred over Antarctica in 2021 as well. The ozone holes developed in smoke-polluted air. In this article, the impact of Siberian and Australian wildfire smoke (dominated by organic aerosol) on the extraordinarily strong ozone reduction is discussed. The study is based on aerosol lidar observations in the North Pole region (October 2019–May 2020) and over Punta Arenas in southern Chile at 53.2∘ S (January 2020–November 2021) as well as on respective NDACC (Network for the Detection of Atmospheric Composition Change) ozone profile observations in the Arctic (Ny-Ålesund) and Antarctica (Neumayer and South Pole stations) in 2020 and 2021. We present a conceptual approach on how the smoke may have influenced the formation of polar stratospheric clouds (PSCs), which are of key importance in the ozone-depleting processes. The main results are as follows: (a) the direct impact of wildfire smoke below the PSC height range (at 10–12 km) on ozone reduction seems to be similar to well-known volcanic sulfate aerosol effects. At heights of 10–12 km, smoke particle surface area (SA) concentrations of 5–7 µm2 cm−3 (Antarctica, spring 2021) and 6–10 µm2 cm−3 (Arctic, spring 2020) were correlated with an ozone reduction in terms of ozone partial pressure of 0.4–1.2 mPa (about 30 % further ozone reduction over Antarctica) and of 2–3.5 mPa (Arctic, 20 %–30 % reduction with respect to the long-term springtime mean). (b) Within the PSC height range, we found indications that smoke was able to slightly increase the PSC particle number and surface area concentration. In particular, a smoke-related additional ozone loss of 1–2 mPa (10 %–20 % contribution to the total ozone loss over Antarctica) was observed in the 14–23 km PSC height range in September–October 2020 and 2021. Smoke particle number concentrations ranged from 10 to 100 cm−3 and were about a factor of 10 (in 2020) and 5 (in 2021) above the stratospheric aerosol background level. Satellite observations indicated an additional mean column ozone loss (deviation from the long-term mean) of 26–30 Dobson units (9 %–10 %, September 2020, 2021) and 52–57 Dobson units (17 %–20 %, October 2020, 2021) in the smoke-polluted latitudinal Antarctic belt from 70–80∘ S.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

HF Doppler observations of acoustic waves excited by the earthquake

Ionospheric disturbances caused by the earthquake of a relatively small and large epicentral distance have been detected by a network of HF-Doppler sounders in central Japan and Kyoto station, respectively. The HF-Doppler data of a small epicentral distance, together with the seismic data, have been used to formulate a mechanism whereby ionospheric disturbances are produced by the Urakawa-Oki earthquake in Japan. Comparison of the dynamic spectra of these data has revealed experimentally that the atmosphere acts as a low-pass filter for upward-propagating acoustic waves. By surveying the earthquakes for which the magnitude M is larger than 6.0, researchers found the ionospheric effect in 16 cases of 82 seismic events. As almost all these effects have occurred in the daytime, it is considered that it may result from the filtering effect of the upward-propagating acoustic waves.

Ichinose, T.↗
NASA NTRS1985

The smallest observable elements of magnetic flux

Time sequences have been used to search for and measure the smallest possible solar flux elements during the process of their disappearance. Measurements are reported of the magnetic flux of 15 of the last remaining visible segments of eight continuously shrinking magnetic features which appeared continuously to cancel with other features of opposite polarity during periods of two to eight hours. The minimum observable fluxes were in the range of 1.0 x 10 to the 16th to 1.4 x 10 to the 17th Mx, and the apparent size of these elements was between 1 and 9 arcsec. The process of disappearance appeared to be a smooth one. The smallest detectable elements of network field and ephemeral regions appeared to be the same as the small intranetwork field elements.

Wang, J.↗
NASA NTRS1987

Cloud-to-ground lightning flash characteristics from June 1984 through May 1985

A magnetic direction-finding network for the detection of lightning cloud-to-ground strikes has been installed along the east coast of the United States. Time, location, flash polarity, stroke count, and peak signal amplitude are recorded in real time. The data were recorded from Maine to North Carolina and as far west as Ohio; analyses were restricted to flashes within 300 km of a direction finder. Measurements of peak signal strength have been obtained from 720,284 first return strokes lowering negative charge. The resulting distribution indicates that few negative strokes have peak currents exceeding 100 kA. Measurements have also been obtained of peak signal strength from 17,694 first return strokes lowering positive charge. These strokes have a median peak current of 45 kA, with some peak currents reaching 300-400 kA. The median peak signal strength and the peak current, double from summer to winter for both negative and positive first return strokes. The polarity of ground flashes is observed to be less than 5 percent positive throughout the summer and early fall, then increases to over 50 percent during the winter, and returns to less than 10 percent in early spring. The percent of positive flashes with one stroke is observed to be approximately 90 percent throughout the year. The percent of negative flashes with one stroke is observed to increase from 40 percent in the summer to approximately 80 percent in January, returning to less than 50 percent in the spring.

Orville, Richard E.↗
NASA NTRS1992

Observation of Stratospheric Ozone with NIES Lidar System in Tsukuba, Japan

Lidars are expected to play important roles in an international monitoring network of the stratosphere such as the Network for the Detection of Stratospheric Change (NDSC). The National Institute for Environmental Studies (NIES) in Tsukuba constructed an ozone lidar system in March 1988 and started observation in August 1988. The lidar system has a 2-m telescope and injection locked XeCl and XeF excimer lasers which can measure ozone profiles (15-45 km) and temperature profiles (30-80 km). From December 1991, lidar observations have been carried out in which the second Stokes line of the stimulated Raman scattering of a KrF laser has been used. Ozone profiles obtained with the NIES lidar system are compared with the data provided by the SAGE II satellite sensor. Results showed good agreement for the individual and the zonal mean profiles. Variations of ozone with various time scales at each altitude can be studied using the data obtained with the NIES ozone lidar system. Seasonal variations are easily found at 20 km, 30 km, and 35 km, which are qualitatively understood as a result of dynamical and photochemical effects. Systematic errors of ozone profiles due to the Pinatubo stratospheric aerosols have been detected using multi-wavelength observation.

Nakane, H.↗
NASA NTRS1991

Remote sensing of atmospheric chemistry; Proceedings of the Meeting, Orlando, FL, Apr. 1-3, 1991

The present volume on remote sensing of atmospheric chemistry discusses special remote sensing space observations and field experiments to study chemical change in the atmosphere, network monitoring for detection of stratospheric chemical change, stratospheric chemistry studies, and the combining of model, in situ, and remote sensing in atmospheric chemistry. Attention is given to the measurement of tropospheric carbon monoxide using gas filter radiometers, long-path differential absorption measurements of tropospheric molecules, air quality monitoring with the differential optical absorption spectrometer, and a characterization of tropospheric methane through space-based remote sensing. Topics addressed include microwave limb sounder experiments for UARS and EOS, an overview of the spectroscopy of the atmosphere using an FIR emission experiment, the detection of stratospheric ozone trends by ground-based microwave observations, and a FIR Fabry-Perot spectrometer for OH measurements.

Mcelroy, James L.↗
NASA NTRS1993

Search for Extraterrestrial Intelligence (SETI)

Various aspects of project SETI are discussed. Some of the topics discussed include spectrum analyzers, signal processing, sky surveys, radiotelescopes, high resolution microwave survey, Deep Space Network, and signal detection.

Billingham, John↗
NASA NTRS1994

Seasonal cycle in atmospheric HCl at 45 deg S

High resolution Fourier transform infrared interferometric atmospheric solar absorption measurements have been performed at the National Institute for Water and Atmospheric Research Laboratory at Lauder, New Zealand on a routine basis since October 1989. This laboratory has been selected as the Mid-latitude Charter Site of the Network for the Detection of Stratospheric Change and is at a latitude of 45 deg S. Particular attention has been paid to the absorption by atmospheric hydrogen chloride at 2925.9 cm(exp -1) and in this paper the results of the seasonal cycle in CHl above Lauder will be presented. Because of the very clean troposphere at this site, the CHl column measured from the ground is essentially a stratospheric column measurement.

Matthews, W. Andrew↗
NASA NTRS1994

Infrared spectroscopic measurements of the ethane (C2H6) total column abundance above Mauna Loa, Hawaii -- seasonal variations

About 200 i.r. solar spectra recorded at 0.01/cm resolution on 71 days between November 1991 and July 1993 at the Network for the Detection of Stratospheric Change (NDSC) station at Mauna Loa, Hawaii (latitude 19.53 deg N, longitude 155.58 deg W, elevation 3.459 km) have been analyzed with a nonlinear least-squares spectral fitting technique to study temporal variations in the total column of atmospheric ethane (C2H6) above the site. The results were derived from the analysis of the unresolved nu(sub 7) band (P)Q(sub 3) subbranch at 2976.8/cm. A distinct seasonal cycle is observed with a factor of 2 variation, a maximum total column of 1.16 x 10(exp 16) mol/sq cm at the end of winter, and a minimum total column of 0.53 x 10(exp 16) mol/sq cm at the end of summer. Our measurements are compared with previous observations and model predictions.

Rinsland, C. P.↗
NASA NTRS1994

Infrared spectroscopic measurements of the total column abundance of ethan (C2H6) above Lauder, New Zealand

Total vertical column aboundances of atmospheric ethane (C2H6) have been retrieved form more than 350 high-resolution infrared solar spectra recorded on 129 days between December 1992 and March 1994 at the Network for the Detection of Stratospheric Change (NDSC) station in Lauder, New Zealand (latitude 45.04 deg S, 169.68 deg E, 0.37 km altitude). The results are based on nonlinear least squares fits to narrow spectral intervals containing the unresolved C2H6 nu (sub 7) band (P)Q(sub 3) and (R)Q(sub 0) subbranches at 2976.8 and 2986.7/cm. The measured Lauder column abundances show a pronounced seasonal cycle with a maximum value of (8.6 +/- 0.5) x 10(exp 15) molecules/sq cm in September and a minimum value of (3.8 +/- 0.5) x 10 (exp 15) molecules/sq cm in February. Assuming a realistic vertical distribution for C2H6, these values correspond to surface level volume-mixing ratios of 0.52 and 0.23 ppbv (parts per billion by volume), respectively. The phase and relative amplitude of the Lauder C2H6 seasonal cycle are similar to corresponding values determined from infrared measurements at the Jungfraujoch (46.55 deg N, 7.98 deg E, 3.58 km altitude) and Mauna Loa (latitude 19.5 deg N, longitude 155.6 deg W, 3.5 km altitude) NDSC stations, but the inferred absolute magnitudes of the Lauder surface level mixing ratios during the same season are significantly lower. The Lauder C2H6 measurements are also compared with published southern hemisphere surface level sampling measurements and two-dimensional model calculations.

Rinsland, Curtis P.↗
NASA NTRS1995

NDSC and JPL stratospheric lidars

The Network for the Detection of Stratospheric Change is an international cooperation providing a set of high-quality, remote-sensing instruments at observing stations around the globe. A brief description of the NDSC and its goals is presented. Lidar has been selected as the NDSC instrument for measurements of stratospheric profiles of ozone, temperature, and aerosol. The Jet Propulsion Laboratory has developed and implemented two stratospheric lidar systems for NDSC. These are located at Table Mountain, California, and at Mauna Loa, Hawaii. These systems, which utilize differential absorption lidar, Rayleigh lidar, raman lidar, and backscatter lidar, to measure ozone, temperature, and aerosol profiles in the stratosphere are briefly described. Examples of results obtained for both long-term and individual profiles are presented.

McDermid, I. Stuart↗